Using Dynamic Partition Mode¶

Let us understand how we can insert data into partitioned table using dynamic partition mode.

Let us start spark context for this Notebook so that we can execute the code provided. You can sign up for our 10 node state of the art cluster/labs to learn Spark SQL using our unique integrated LMS.

val username = System.getProperty("user.name")

import org.apache.spark.sql.SparkSession

val username = System.getProperty("user.name")
val spark = SparkSession.
    builder.
    config("spark.ui.port", "0").
    config("spark.sql.warehouse.dir", s"/user/${username}/warehouse").
    enableHiveSupport.
    appName(s"${username} | Spark SQL - Managing Tables - DML and Partitioning").
    master("yarn").
    getOrCreate

If you are going to use CLIs, you can use Spark SQL using one of the 3 approaches.

Using Spark SQL

spark2-sql \
    --master yarn \
    --conf spark.ui.port=0 \
    --conf spark.sql.warehouse.dir=/user/${USER}/warehouse

Using Scala

spark2-shell \
    --master yarn \
    --conf spark.ui.port=0 \
    --conf spark.sql.warehouse.dir=/user/${USER}/warehouse

Using Pyspark

pyspark2 \
    --master yarn \
    --conf spark.ui.port=0 \
    --conf spark.sql.warehouse.dir=/user/${USER}/warehouse

Using dynamic partition mode we need not pre create the partitions. Partitions will be automatically created when we issue INSERT command in dynamic partition mode.
To insert data using dynamic partition mode, we need to set the property hive.exec.dynamic.partition to true
Also we need to set hive.exec.dynamic.partition.mode to nonstrict

Here is the example of inserting data into partitions using dynamic partition mode.

%%sql

USE itversity_retail

%%sql

SHOW tables

%%sql

SELECT count(1) FROM orders

%%sql

SELECT count(1) FROM orders_part

%%sql

SET hive.exec.dynamic.partition

%%sql

SET hive.exec.dynamic.partition.mode

%%sql

SET hive.exec.dynamic.partition=true

%%sql

SET hive.exec.dynamic.partition.mode=nonstrict

%%sql

INSERT INTO TABLE orders_part PARTITION (order_month)
SELECT o.*, date_format(order_date, 'yyyyMM') order_month
FROM orders o
WHERE order_date >= '2013-12-01 00:00:00.0'

import sys.process._

s"hdfs dfs -ls -R /user/${username}/warehouse/${username}_retail.db/orders_part" !

%%sql

SELECT count(1) FROM orders

%%sql

SELECT count(1) FROM orders_part

You will see new partitions created starting from 201312 to 201407.

Apache Spark using SQL

Using Dynamic Partition Mode¶